Senior Software Engineer

At Dice, we believe that delivering an exceptional candidate experience — the end-to-end journey a job seeker takes to discover, evaluate, and land their next role — is essential to the success of our platform. This team plays a critical role in building the next generation of that experience, contributing across a modern full-stack environment. We value engineers who are curious, collaborative, and committed to making an impact for thousands of job seekers.

We are an AI-native team. We actively use AI coding assistants (e.g., Claude Code, Codex, Gemini CLI) to accelerate development, sharpen code quality, and focus our energy on higher-impact engineering work.

As a Senior Software Engineer at Dice, you’ll contribute to the design, development, and delivery of high-impact product features in a modern, cloud-native stack. As a senior engineer you’ll be expected to provide technical leadership within the team by driving architectural decisions, mentoring teammates, and helping maintain a high standard of quality and maintainability. You’ll collaborate cross-functionally with Product, Design, and Data partners to align on outcomes and advocate for sound technical solutions.

Being AI-native is central to how we work. We expect engineers in this role to go beyond using AI as a simple chat assistant, embracing tools like Claude Code as core parts of the development workflow to increase productivity such as automating repetitive tasks by generating skills and leveraging subagents, and apply best practices through prompt engineering to get the most out of the AI tools we use at every stage of the software lifecycle.

As we scale and modernize our platform, we’re looking for experienced senior engineers who can take ownership of complex systems, communicate effectively with stakeholders, deploy AI-powered features, and contribute to product and architectural decisions. This role is ideal for someone who enjoys working across the stack, solving real user problems, working with AI, and influencing both code and culture.

In the Short Term, You Will:

Gain familiarity with our applications, services, tools, and infrastructure. Develop an understanding of how your team’s work fits into the broader product and architecture.

Take responsibility for features and systems, provide thoughtful code reviews, and contribute to team design discussions. You’ll be trusted to make solid technical decisions and defend them clearly when needed while staying open to feedback.

Work closely with engineers, product managers, designers, and stakeholders to align on priorities and deliver incremental value. Help improve the team's planning and execution rhythm.

In the Long Term, You Will:

Help evolve our systems through well-designed, scalable AI architecture. Reduce tech debt, improve performance, and contribute to shared engineering standards.

The Senior Software Engineer at Dice plays a key role in mentoring peers, reviewing designs, and helping grow the technical capabilities of those around you.

Own end-to-end delivery of AI-powered product features that support business goals and enhance user experience. Influence the roadmap by advocating for technical investments that align with long-term value.

• Proven experience building and deploying production-grade applications with a track record of delivering value through practical, maintainable solutions
• Strong technical skills and experience in cloud-based technologies
• Track record of development and deployment of ML and AI features into a Production environment.
• Ability to navigate ambiguity, make sound decisions, and adapt to changing priorities
• A collaborative, team-first mindset — you know the best outcomes come from working well together, and you actively contribute to a supportive, inclusive team environment
• Technical depth and experience that allows you to lead design discussions, break down complex tasks into meaningful deliverables, and ensure a high standard of engineering quality
• A sense of urgency, accountability, and ownership, you take pride in your work and team achievements.
• Strong communication, problem-solving, and collaboration skills, with the confidence to advocate for ideas while being open to alternative perspectives

• Proven experience building and maintaining business-critical applications using Node.js and TypeScript in a production setting
• Hands-on experience developing scalable, maintainable RESTful and GraphQL services in production environments
• Working knowledge of container-based technologies (Docker, Fargate, Kubernetes, or other)
• Experience with front-end frameworks such as NextJS, React, or Angular
• Demonstrated experience building highly available applications on AWS infrastructure
• Experience implementing and working with CI/CD pipelines to support automated testing and deployments
• Ability to apply quality best practices and implement automated testing using tools such as Playwright
• Solid understanding of architectural patterns (event-driven, serverless, SOA, and others)
• Practical understanding of how to implement traditional Machine Learning models and LLMs in production, including knowledge of model selection criteria and architectural trade-offs
• Hands-on experience deploying LLM-powered features into production, such as simple LLM API calls, RAG (Retrieval-Augmented Generation) systems, Vector Stores, and MCP Servers
• Familiarity with AI/ML tooling such as LangChain, LangGraph, LangSmith, Vercel AI SDK, LiteLLM, or equivalent frameworks

• Understanding of different programming paradigms such as OOP and Functional
• Experience with highly available, highly scalable SaaS applications
• Working knowledge of logging and observability best practices
• Familiarity with DevOps principles and the ability to work closely with platform teams
• Knowledge of performance tuning, cost optimization, or scalability in a cloud-native environment
• Comfort navigating ambiguity to define and implement technical solutions
• Experience collaborating with cross-functional partners (Product, Design, Data)
• Experience designing and deploying Agentic features or autonomous AI Agents in a production environment
• Experience with LLM evaluation techniques (e.g., LLMs-as-judges), prompt engineering, and context engineering
• Familiarity with LLM guardrails and safeguards, monitoring, and observability practices for production AI systems
• Experience working as an AI-native engineer — including creating agent skill files, configuring and orchestrating subagents, or building custom AI tooling to accelerate engineering workflows

NOTE: This job description is not intended to be an all-inclusive list of the duties and responsibilities of the job described, nor are they intended to be such a listing of the skills and abilities required to do the job. Rather, they are intended only to describe the general nature of the job as of the date this job description was prepared. Management reserves the right to modify this job in order to meet business needs. 

You can apply below. You'll just need to provide your resume and answer a few questions—it'll only take you a few minutes!

All qualified applicants will receive consideration for employment without regard to age, race, color, religion, sex, sexual orientation, gender identity, national origin, disability, or status as a protected veteran.